```
---
title: "dashboard"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
source: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(plotly)
library(p8105.datasets)
data("ny_noaa")
```
```{r}
# Limit the weather data to 2000 from the main data set
# Data cleaning; select observations with non-zero snowfalls and also limit to 200 snowfall.
ny_noaa_df=
ny_noaa %>%
janitor::clean_names() %>%
drop_na() %>%
separate(col = date, into = c ("year", "month", "day") , sep = "-", convert = TRUE) %>%
mutate(snowfall = snow*25.4,
month = month.abb[month],
tmax = as.numeric(tmax) / 10,
tmin = as.numeric(tmin) / 10) %>%
filter(snow > 0, snow < 200, year == 2000) %>%
select(id, year, month, day, snowfall, tmax, tmin)
```
Column {data-width=650}
-----------------------------------------------------------------------
### Chart A: New York Station's Snowfalls in 2000
```{r}
ny_noaa_df %>%
mutate(month = fct_reorder(month, snowfall)) %>%
plot_ly(y = ~snowfall, color = ~month, type = "box", colors = "viridis") %>%
layout(xaxis = list(title = 'Month'),
yaxis = list(title = 'Snowfall (mm)'))
```
Column {data-width=350}
-----------------------------------------------------------------------
### Chart B: New York Station's Monthly Mininum and Maximum Temperature in 2000
```{r}
ny_noaa_df %>%
plot_ly(x = ~tmin, y = ~tmax, color = ~month, opacity=0.5, colors = "viridis") %>%
layout(xaxis = list(title = 'Mininum Temperature'),
yaxis = list(title = 'Maximum Temperature'))
```
### Chart C: New York Station's Snowy Days Frequency in 2000
```{r}
ny_noaa_df %>%
count(id) %>%
mutate(id = fct_reorder(id, n)) %>%
plot_ly(x = ~id, y = ~n, color = ~id, type = "bar", colors = "viridis") %>%
layout(xaxis = list(title = 'Weather station ID'),
yaxis = list(title = 'Number Snowy Days'))
```
```